Forensic Y-SNP analysis beyond SNaPshot: High-resolution Y-chromosomal haplogrouping from low quality and quantity DNA using Ion AmpliSeq and targeted massively parallel sequencing

Clean tree v2

Arwin Ralf, Mannis van Oven, Diego Montiel González, Sharon Wooten, Robert Lagace, Peter de Knijff, and Manfred Kayser

Department of Genetic Identification

Erasmus MC University Medical Centre Rotterdam, The Netherlands

Requirements

Operating system: Linux only. Tested on Ubuntu 16.04LTS, but should also work on newer version of Ubuntu. It should be easy to made it work on other Linux distributions. 
Python, wget
Internet connection during installation (for downloading and extracting hg19 reference genome).
Data storage: For installation we recommend a storage capacity of > 10 GB. 

Installation

1. Install dependencies, you can skip this step if these packages are already installed on your system

    apt-get install python3.6             
        apt-get install mawk 
        apt-get install p7zip-full 
        apt-get install bwa
   

   -SAMtools We recommend the newests versions of SAMtools (e.g. > 1.4.1)

        1. wget https://github.com/samtools/samtools/releases/download/1.4.1/	samtools-1.4.1.tar.bz2 -O samtools.tar.bz2
        2. tar -xjvf samtools.tar.bz2 
        3. cd samtools-1.4.1/
        4. ./configure
        5. make
        6. make install
   

Usage example for Clean Tree (BAM format)

    python clean_tree.py -bam file.bam -pos data/positions.txt -out out -r 1 -q 20 -b 95

Usage for haplogroup prediction

python predict_haplogroup.py -input Output_files/ -out output.hg

4. See complete manual at the website: https://www.erasmusmc.nl/genetic_identification/resources/

5. Bug report

Please email me at d.montielgonzalez@erasmusmc.nl when there is a problem getting the software up and running.

References and Supporting Information

A. Ralf, et al., Forensic Y-SNP analysis beyond SNaPshot: High-resolution Y-chromosomal haplogrouping from low quality and quantity DNA using Ion AmpliSeq and targeted massively parallel sequencing (2019).

https://doi.org/10.1016/j.fsigen.2019.04.001